Multi-Region Optimal Scheduling Strategy for Electric Vehicles Considering Compensation Incentives

doi:10.16183/j.cnki.jsjtu.2022.348

Abstract

Abstract:

Aimed at the problem of uneven supply and distributed renewable energy (DRE) in charging regions and electric vehicle (EV) loads, a multi-region optimal scheduling strategy for EVs considering compensation incentives is proposed to guide EVs to choose different charging regions, so as to promote local consumption of distributed energy. First, an EV charging response model is established based on the price elasticity of demand and users’ time anxiety. Then, based on the principle of remaining power availability and idle time redundancy, EVs are divided into responsive cluster and non-responsive cluster. A charging area decision model based on regret theory is used to further divide the responsive cluster by region. Finally, a multi-region optimal scheduling model for EVs is established, and the charging price is optimized in terms of maximizing the economic benefits of charging service providers and the consumption of DRE. Simulation cases show that the proposed optimization strategy can fully consider the impact of time anxiety and price elasticity on EV users, fully tap the users’ response potential, and has obvious effects in reducing the deviation of distributed new energy consumption and improving the economic benefits of charging service providers.

Key words: electric vehicle (EV), distributed renewable energy (DRE), charging compensation, time anxiety

CLC Number:

TM732

SUN Yi, GE Mingyang, WANG Xianchun, BAO Huiyu, YANG Hongyue, YAO Tao. Multi-Region Optimal Scheduling Strategy for Electric Vehicles Considering Compensation Incentives[J]. Journal of Shanghai Jiao Tong University, 2024, 58(5): 636-646.

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EV位置信息	距离区域1的路程/km	距离区域2的路程/km	距离区域3的路程/km
靠近区域1	2~4	4~6	6~8
靠近区域2	4~6	2~4	4~6
靠近区域3	6~8	4~6	2~4

时段	外购电价	DRE电价	充电单价
峰 8:00—12:00 17:00—21:00	0.65	0.45	1.082
平 12:00—17:00 21:00—24:00	0.40	0.30	0.649
谷 0:00-8:00	0.30	0.22	0.316

调度策略	服务商收益/ 万元	DRE消纳偏差	用户单位充电成本/元
对比策略1	1.3976	60.54	0.8704
对比策略2	1.4003	35.68	0.8536
对比策略3	1.4334	24.46	0.8246
对比策略4	1.4218	31.57	0.8378
本文策略	1.5387	20.76	0.8084

EV编号	策略	时间后悔值			价格后悔值			总后悔值			决策结果
EV编号	策略	区域1	区域2	区域3	区域1	区域2	区域3	区域1	区域2	区域3	决策结果
1	对比策略4	1.53	0.89	0.00	0.00	1.50	3.18	0.00	0.86	1.65	1
1	本文策略	1.53	0.89	0.00	0.00	1.77	3.66	0.00	1.13	2.13	1
6	对比策略4	1.91	1.20	0.00	0.00	0.92	1.28	0.63	0.84	0.00	3
6	本文策略	1.91	1.20	0.00	0.00	1.02	1.71	0.20	0.51	0.00	3
7	对比策略4	1.58	0.88	0.00	0.00	0.97	1.27	0.31	0.58	0.00	3
7	本文策略	1.58	0.88	0.00	0.00	1.53	3.21	0.00	0.83	1.63	1
15	对比策略4	1.12	0.56	0.00	0.00	0.73	0.91	0.21	0.38	0.00	3
15	本文策略	1.12	0.56	0.00	0.00	1.13	2.57	0.00	0.57	1.45	1

EV 数量	调度策略	充电服务商收益/万元	消纳偏差	用户单位充电成本/元
1倍	对比策略3	1.4274	25.16	0.8198
1倍	对比策略4	1.4178	30.27	0.8343
1倍	本文策略	1.5167	21.36	0.8041
1.25倍	对比策略3	1.6629	26.79	0.8218
1.25倍	对比策略4	1.6332	31.36	0.8378
1.25倍	本文策略	1.7976	22.08	0.8112
1.5倍	对比策略3	1.9175	35.32	0.8234
1.5倍	对比策略4	1.8654	41.78	0.8402
1.5倍	本文策略	1.9821	32.45	0.8175